[1]朱晓东,刘丹,李广.基于混合优化算法的模糊系统辨识[J].郑州大学学报(工学版),2015,36(04):10-14.[doi:10.3969/ j. issn.1671 -6833.2015.04.003]
　ZHU Xiao-dong,LIU Dan,Ll Guang.ldentification of Hierarchical Fuzzy System Based on HybridOptimization Algorithm[J].Journal of Zhengzhou University (Engineering Science),2015,36(04):10-14.[doi:10.3969/ j. issn.1671 -6833.2015.04.003]
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基于混合优化算法的模糊系统辨识()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
36
期数:
2015年04期
页码:
10-14
栏目:
出版日期:
2015-08-31

文章信息/Info

Title:
ldentification of Hierarchical Fuzzy System Based on HybridOptimization Algorithm
作者:
朱晓东; 刘丹; 李广
郑州大学电气工程学院,河南郑州450001
Author(s):
ZHU Xiao-dong; LIU Dan; Ll Guang
School of Electrical Engineering, Lhengzhou University , Lhengzhou 450001 , China
关键词:
分层模糊系统; 粒子群优化算法; 递推最小二乘法
Keywords:
hierarchical fuzzy system;  particle swarm optimization algorithm; recursive least square algorithm
分类号:
TP273
DOI:
10.3969/ j. issn.1671 -6833.2015.04.003
文献标志码:
A
摘要:
针对一种新型分层模糊系统,提出了一种混合优化算法,即利用粒子群优化算法辨识每一个模糊单元模型的前件参数,利用递推最小二乘算法辨识后件参数.采用该辨识方法对Mackey-Glass 混沌时间序列及Box-Jenkins 数据进行实验,并与果蝇优化算法以及入侵杂草优化算法的仿真结果进行了比较,实验结果表明:这种混合优化算法能够提高分层模糊系统模型的精度.
Abstract:
In view of a new type of hierarchical fuzny system,a hybrid optimization algorithm is proposed inthis paper. The antecedent parameters of each fuzzy unit model are estimated by the particle swarm optimiza-tion algorithm,and the recursive least square algorithm is used to determine the parameters of consequents.Experiments on the well-known Box-Jenkins set data and the chaotic Mackey-Glass time series are carried out.The proposed hybrid optimization algorithm is compared with the fruit fly optimization algorithm and the inva-sive weed optimization algorithm. The result of experiments shows that the hybrid optimization algorithm canimprove the accuracy of the hierarchical fuzzy system model.

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